Object of class "character" that defaults to
algorithm="nls", so that the function nls is used to
optimize nonlinear parameters under least squares criteria.
Other options are

nls.lm:

optim:

optimize nonlinear parameters under poisson
regression criteria with the Nelder-Mead algorithm in
optim; if this option is used then it MUST be used in
conjunction with nnls=TRUE. Currently, it must also be
used with stderrclp=FALSE.

nnls:

Object of class "logical" that defaults to
FALSE. If nnls=TRUE,
constrain the conditionally linear parameters
to nonnegativity via a nonnegative least squares algorithm as
implemented via the function nnls from the package by the same
name.

writecon:

Object of class "logical" that defaults to
FALSE; if true then
concentrations are written to a txt file; row labels are x

writespec:

Object of class "logical" that defaults to
FALSE; if TRUE then
spectra are written to a txt file; row labels are x2

writenormspec:

Object of class "logical" that
defaults to FALSE; if TRUE then normalized spectra are
written to a txt file; row labels are x2

writefit:

Object of class
"logical" that defaults to FALSE; if TRUE then fit
is written to a txt file; row and column labels are x and
x2

writeclperr:

Object of class "logical"
that defaults to
FALSE; if true then
the error bars for clp are written to a txt file. This option is only
sensible with stderrclp=TRUE.

output:

Object of class
"character" that defaults to "ps", which means that
plots written to file are postscript. Alternatively, specify
output = "pdf", and plots are written as pdf files

addfilename:

Object of class
"logical" that, for each data file, tries to add the
filename to plots associated with output for that data.

residplot:

Object of class "logical" defaults to
FALSE; if TRUE generate a plot of residuals in a
separate window.

adddataimage:

Object of class "logical" defaults to
FALSE; if TRUE adding imageplot of data in summary plot.

plot:

Object of class "logical" that defaults to
TRUE; if FALSE then do not write output in the form of
plots and other windows to the screen.

divdrel:

Object of class "logical" that defaults to
FALSE; if TRUE, plot traces and concentration
profiles divided by the dataset scaling parameters where they apply; this
allows for the fit of datasets having different intensities on the same
scale.

plotkinspec:

Object of class "logical" that defaults
to FALSE; if TRUE, generates a separate plot of the spectra
associated with the components that are not a part of a coherent
artifact/scatter model.

xlab:

ylab:

title:

Object of class "character" containing title
to write at the top of plots.

makeps:

Object of class "character" containing
prefix to plot files written to postscript;
if present postscript will be written. Note that this string is also
used as the preffix of txt output files

linrange:

Object of class "numeric" giving linear
range of time axis for plotting; time will be plotted linearly from
-linrange to linrange and plotted on a logarithmic (base 10) axis elsewhere

summaryplotrow:

Object of class "numeric" giving
number of rows in summary plot; defaults to 4

summaryplotcol:

Object of class "numeric" giving
number of columns in summary plot; defaults to 4

iter:

Object of class "numeric" giving
number of iterations to optimize model parameters; if
nls=FALSE so that the Levenberg-Marquardt algorithm is
applied, then iter is interpretted as the
maximum number of residual function evaluations (see the help
page of the function nls.lm for details)

paropt:

Object of class "list"
of graphical parameters in format par(...)
to apply to plots.

stderrclp:

Object of class "logical" that defaults
to FALSE; if TRUE, estimates of the standard error of
conditionally linear parameters are made

addest:

Object of class "vector" containing
character strings of which parameter estimates should be added to the
summary plot, e.g., addest = c("kinpar", "irfpar")

kinspecerr

Object of class "logical" that defaults to
FALSE; if TRUE, add standard error estimates to the clp
a plot generated with kinspecest=TRUE or
plotkinspec=TRUE. This option can only be
used if the estimates were generated during fitting via the option
stderrclp=TRUE

xlimspec

Object of class "vector" that defaults to
vector(); if changed, it should specify the desired x-limits of
the plot of clp

ylimspec

Object of class "vector" that defaults to
vector(); if changed, it should specify the desired y-limits of
the plot of clp. In the case of plotting the results of FLIM image
analysis, ylimspec can be used to determine the range used in the
image plot of lifetimes.

ylimspecplus

Object of class "vector" that defaults to
vector(); if changed, the first value should specify a vector to
add to the y-limits of the plot of clp

samespecline

Object of class "logical" that defaults to
FALSE; if TRUE, then the line-type for clp is the same
for all datasets

specinterpol

Object of class "logical" that defaults to
FALSE; if TRUE, use spline instead of lines between
the points representing estimated clp

specinterpolpoints

Object of class "logical" that defaults to
TRUE; if TRUE, add points representing the actual estimates
for clp to plots of the curves respresenting smoothed clp

specinterpolseg

Object of class "numeric" that defaults to
50; represents the number of segments used in a spline-based
representation of clp

specinterpolbspline

Object of class "logical" that defaults
to FALSE; determines whether a B-spline based representation of
clp is used (when specinterpol=TRUE) or a piecewise polynomial
representation

normspec

Object of class "logical" that determines whether
clp are normalized in plots

writespecinterpol

Object of class "logical" that defaults to
FALSE; if TRUE, a spline-based representation of clp
is written to ASCII files

nlsalgorithm

Object of class "character" that defaults to
"default" and determines the algorithm used by nls, if
nls is used in optimization. See help(nls) for other
possibilities, such as "port", which is more stable with
respect to starting values but requires more time.

ltyfit

Object of class "numeric" if given, sets the line
type of the fit in plots of the fit/data; see lty in
help(par) for options.

ltydata

Object of class "numeric" if given, sets the line
type of the data in plots of the fit/data; see lty in
help(par) for options.

colfit

Object of class "vector" if given, sets the color
of the fit corresponding to each dataset
in plots of the fit/data; see col in
help(par) for options. If given
length(colfit) must be equal to
the number of datasets in the analysis

coldata

Object of class "vector" if given, sets the color
of the data for each dataset
in plots of the fit/data; see col in
help(par) for options. If given,
length(coldata) must be equal to
the number of datasets in the analysis